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Abstract The frequency and intensity of summer extreme climate events are increasing over time, and have a substantial negative effect on plants, which may be evident in their impact on photosynthesis. Here, we examined the photosynthetic responses of Larix kaempferi and Pinus densiflora seedlings to extreme heat (+ 3 °C and + 6 °C), drought, and heavy rainfall by conducting an open-field multifactor experiment. Leaf gas exchange in L. kaempferi showed a decreasing trend under increasing temperature, showing a reduction in the stomatal conductance, transpiration rate, and net photosynthetic rate by 135.2%, 102.3%, and 24.8%, respectively, in the + 6 °C treatment compared to those in the control. In contrast, P. densiflora exhibited a peak function in the stomatal conductance and transpiration rate under + 3 °C treatment. Furthermore, both species exhibited increased total chlorophyll contents under extreme heat conditions. However, extreme precipitation had no marked effect on photosynthetic activities, given the overall favorable water availability for plants. These results indicate that while extreme heat generally reduces photosynthesis by triggering stomatal closure under high vapor pressure deficit, plants employ diverse stomatal strategies in response to increasing temperature, which vary among species. Our findings contribute to the understanding of mechanisms underlying the photosynthetic responses of conifer seedlings to summer extreme climate events.

Abstract Despite the importance of agroforestry parkland systems for ecosystem and livelihood benefits, evidence on determinants of carbon storage in parklands remains scarce. Here, we assessed the direct and indirect influence of human management (selective harvesting of trees), abiotic factors (climate, topography, and soil) and multiple attributes of species diversity (taxonomic, functional, and structural) on aboveground carbon (AGC) stocks in 51 parklands in drylands of Benin. We used linear mixed-effects regressions and structural equation modeling to test the relative effects of these predictors on AGC stocks. We found that structural diversity (tree size diversity, HDBH) had the strongest (effect size β = 0.59, R2 = 54%) relationship with AGC stocks, followed by community-weighted mean of maximum height (CWMMAXH). Taxonomic diversity had no significant direct relationship with AGC stocks but influenced the latter indirectly through its negative effect on CWMMAXH, reflecting the impact of species selection by farmers. Elevation and soil total organic carbon content positively influenced AGC stocks both directly and indirectly via HDBH. No significant association was found between AGC stocks and tree harvesting factor. Our results suggest the mass ratio, niche complementarity and environmental favorability as underlying mechanisms of AGC storage in the parklands. Our findings also highlight the potential role of human-driven filtering of local species pool in regulating the effect of biodiversity on AGC storage in the parklands. We conclude that the promotion of AGC stocks in parklands is dependent on protecting tree regeneration in addition to enhancing tree size diversity and managing tall-stature trees.

Afforestation of the desiccated Aral Sea Bed is needed for the rapid introduction of vegetation and rehabilitation of the soil environment. The present study aimed to detect the soil amelioration effect by afforestation of the Aral Sea Bed with respect of changes in topsoil properties and enzyme activities. In August and November 2018, soils were sampled from the barren areas and from areas afforested in 1991, 2005, 2009, 2010, and 2013. The exchangeable base cation concentrations (Ca2+, K+, Mg2+, and Na+), cation exchange capacity (CEC), plant-available P concentration, electrical conductivity, pH, and enzyme activities (acid phosphatase, β-glucosidase, and N-acetyl-glucosaminidase) were analyzed in the surface soil (0–10 cm). Base cation concentrations, CEC, and electrical conductivity decreased following afforestation possibly because of root absorption. The observed increase in soil pH could be affected by both root absorption and decomposition of plant residues. Enzyme activities, which are early indicators of soil recovery, might have been increased by afforestation through the release of nutrients from litter and root exudates. Our findings indicate that the establishment of vegetation through afforestation can provide supportive microenvironments for plants and microorganisms by decreasing soil salinity and activating soil microbial enzymes; these effects of afforestation are amplified over time.

Abstract Despite rapid advances and large-scale initiatives in forest mapping, reliable cross-border information about the status of forest resources in Central Asian countries is lacking. We produced consistent Central Asia forest cover (CAFC) maps based on a cost-efficient approach using multi-resolution satellite imagery from Landsat and MODIS during 2009–2011. The spectral-temporal metrics derived from 2009–2011 Landsat imagery (overall accuracy of 0.83) was used to predict sub-pixel forest cover on the MODIS scale for 2010. Accuracy assessment confirmed the validity of MODIS-based forest cover map with a normalized root-mean-square error of 0.63. A general paucity of forest resources in post-Soviet Central Asia was indicated, with 1.24% of the region covered by forest. In comparison to the CAFC map, a regional map derived from MODIS Vegetation Continuous Fields tended to underestimate forest cover, while the Global Forest Change product matched well. The Global Forest Resources Assessments, based on individual country reports, overestimated forest cover by 1.5 to 147 times, particularly in the more arid countries of Turkmenistan and Uzbekistan. Multi-resolution imagery contributes to regionalized assessment of forest cover in the world’s drylands while developed CAFC maps (available at https://data.zef.de/ ) aim to facilitate decisions on biodiversity conservation and reforestation programs in Central Asia.

Acquiring multi-temporal spatial information on vegetation condition at scales appropriate for site-specific agricultural management is often complicated by the need for meticulous field measurements. Understanding spatial/temporal crop cover heterogeneity within irrigated croplands may support sustainable land use, specifically in areas affected by land degradation due to secondary soil salinization. This study demonstrates the use of multi-temporal, high spatial resolution (10 m) SPOT-4/5 image data in an integrated change vector analysis and spectral mixture analysis (CVA-SMA) procedure. This procedure was implemented with the principal objective of mapping sub-field vegetation cover dynamics in irrigated lowland areas within the lowerlands of the Amu Darya River. CVA intensity and direction were calculated separately for the periods of 1998–2006 and 2006–2010. Cumulative change intensity and the overall directional trend were also derived for the entire observation period of 1998–2010. Results show that most of the vector changes were observed between 1998 and 2006; persistent conditions were seen within the study region during the 2006–2010 period. A decreasing vegetation cover trend was identified within 38% of arable land. Areas of decreasing vegetation cover were located principally in the irrigation system periphery where deficient water supply and low soil quality lead to substandard crop development. During the 2006–2010 timeframe, degraded crop cover conditions persisted in 37% of arable land. Vegetation cover increased in 25% of the arable land where irrigation water supply was adequate. This high sub-field crop performance spatial heterogeneity clearly indicates that current land management practices are inefficient. Such information can provide the basis for implementing and adapting irrigation applications and salt leaching techniques to site-specific conditions and thereby make a significant contribution to sustainable regional land management.

Accurate monitoring of land surface dynamics using remote sensing is essential for the synoptic assessment of environmental change. We assessed a Medium Resolution Imaging Spectrometer (MERIS) full resolution dataset for vegetation monitoring as an alternative to the more commonly used Moderate-Resolution Imaging Spectroradiometer (MODIS) data. Time series of vegetation indices calculated from 300 m resolution MERIS and 250 m resolution MODIS datasets were analyzed to monitor vegetation productivity trends in the irrigated lowlands in Northern Uzbekistan for the period 2003–2011. Mann-Kendall trend analysis was conducted using the time series of Normalized Differenced Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), and MERIS-based Terrestrial Chlorophyll Index (MTCI) to detect trends and examine the capabilities of each sensor and index. The methodology consisted of (1) preprocessing of the original imagery; (2) processing and statistical analysis of the corresponding time series datasets; and (3) comparison of the resulting trends. Results confirmed the occurrence of widespread vegetation productivity decline, ranging from 5.5% (MERIS-MTCI) to 21% (MODIS-NDVI) of the total irrigated cropland in the study area. All indices identified the same spatial patterns of decreasing vegetation. Average vegetation index values of NDVI and SAVI were slightly higher when measured by MERIS than by MODIS. These differences merit further investigation to allow a fusion of these datasets for consistent monitoring of cropland productivity decline at scales suitable for guiding operational land management practices.

This study analyzes the impact of land use/land cover (LULC) changes on the hydrology of the dry Afromontane forest landscape in northern Ethiopia. Landsat satellite images of thematic mapper (TM) (1986), TM (2001), and Operational Land Imager (OLI) (2018) were employed to assess LULC. All of the images were classified while using the maximum likelihood image classification technique, and the changes were assessed by post-classification comparison. Seven LULC classes were defined with an overall accuracy 83−90% and a Kappa coefficient of 0.82−0.92. The classification result for 1986 revealed dominance of shrublands (48.5%), followed by cultivated land (42%). Between 1986 and 2018, cultivated land became the dominant (39.6%) LULC type, accompanied by a decrease in shrubland to 32.2%, as well as increases in forestland (from 4.8% to 21.4%) and bare land (from 0% to 0.96%). The soil conservation systems curve number model (SCS-CN) was consequently employed to simulate forest hydrological response to climatic variations and land-cover changes during three selected years. The observed changes in direct surface runoff, the runoff coefficient, and storage capacity of the soil were partially linked to the changes in LULC that were associated with expanding bare land and built-up areas. This change in land use aggravates the runoff potential of the study area by 31.6 mm per year on average. Runoff coefficients ranged from 25.3% to 47.2% with varied storm rainfall intensities of 26.1−45.4 mm/ha. The temporal variability of climate change and potential evapotranspiration increased by 1% during 1981−2018. The observed rainfall and modelled runoff showed a strong positive correlation (R2 = 0.78; p < 0.001). Regression analysis between runoff and rainfall intensity indicates their high and significant correlation (R2 = 0.89; p < 0.0001). Changes were also common along the slope gradient and agro-ecological zones at varying proportions. The observed changes in land degradation and surface runoff are highly linked to the change in LULC. Further study is suggested on climate scenario-based modeling of hydrological processes that are related to land use changes to understand the hydrological variability of the dry Afromontane forest ecosystems.

Abstract  This paper evaluates the potential of nine multipurpose tree species for afforestation of degraded land in the Khorezm region, Central Asia, particularly their suitability for biodrainage i.e., lowering the elevated groundwater table through the transpirative capacity of plantations. For this purpose water use (WU), water use efficiency (WUE) and tree physiological factors influencing transpiration were assessed during two consecutive years. Mean daily leaf transpiration differed significantly among the species and ranged during the seasons from 4.5–5.2 mmol m−2 s−1 for Prunus armeniaca L. to 4.5–10 mmol −2 s−1 for Elaeagnus angustifolia L. WU differences were triggered by species physiological features such as capability of water uptake by roots. Transpiration rates and the length of fine roots correlated highly (r = 0.7). Correlations of leaf transpiration rates with leaf area were weaker (r = 0.6). No correlations were found between salt content in plants and water uptake under conditions of slight-to-moderate rootzone soil salinity. Values of WUE per root and shoot DM were similar averaging, respectively, 0.2 and 0.3 g DM g−1 water for two-year-old trees, and decreased with age. In addition to WU characteristics, also salinity tolerance, growth rate and the ability to produce fodder and fuelwood must be considered during species selection. Regarding these features, the N-fixing E. angustifolia ranked the highest, combining high WU, fast growth and production of nutritious feed. Examined Populus spp. and Ulmus pumila L. ranked lower but still represented potential candidates for biodrainage purposes. Typical fruit species in the region such as P. armeniaca and Morus alba, showed low biodrainage potential. [ABSTRACT FROM AUTHOR]